Integrated production and outbound distribution scheduling problems with job release dates and deadlines
- 286 Downloads
In this paper, we study an integrated production and outbound distribution scheduling model with one manufacturer and one customer. The manufacturer has to process a set of jobs on a single machine and deliver them in batches to the customer. Each job has a release date and a delivery deadline. The objective of the problem is to issue a feasible integrated production and distribution schedule minimizing the transportation cost subject to the production release dates and delivery deadline constraints. We consider three problems with different ways how a job can be produced and delivered: non-splittable production and delivery (NSP–NSD) problem, splittable production and non-splittable delivery problem and splittable production and delivery problem. We provide polynomial-time algorithms that solve special cases of the problem. One of these algorithms allows us to compute a lower bound for the NP-hard problem NSP–NSD, which we use in a branch-and-bound (B&B) algorithm to solve problem NSP–NSD. The computational results show that the B&B algorithm outperforms a MILP formulation of the problem implemented on a commercial solver.
KeywordsSingle machine scheduling Production and delivery Release dates Deadlines Transportation costs Branch-and-bound
This work was partially funded by ANR, the French National research agency (ATHENA project, reference ANR-13-BS02-0006).
- European Commission. (2011). Road Freight Transport Vademecum 2010 Report. Last visited January, 2017 http://ec.europa.eu/transport/sites/transport/files/modes/road/doc/2010-road-freight-vademecum.pdf.
- Feng, X., Cheng, Y., Zheng, F., & Xu, Y. (2016). Online integrated production–distribution scheduling problems without preemption. Journal of Combinatorial Optimization, 31(4), 1569–1585.Google Scholar
- Garey, M., & Johnson, D. (1979). Computers and intractability: A guide to the theory of NP-completeness. New York: W.H Freeman.Google Scholar
- Graham, R. L., Lawler, E. L., Lenstra, J. K., & Rinnooy Kan, A. H. G. (1979). Optimization and approximation in deterministic sequencing and scheduling: A survey. In E. J. P. L. Hammer & B. Korte (Eds.), Discrete optimization II, annals of discrete mathematics (Vol. 5, pp. 287–326). Amsterdam: Elsevier.Google Scholar
- Hall, L. A., & Shmoys, D. B. (1989). Approximation algorithms for constrained scheduling problems. In Proceedings of the 30th annual symposium on foundations of computer science (pp. 134–140).Google Scholar
- Jackson, J. R. (1955). Scheduling a production line to minimize maximum tardiness. Technical report, University of California, Los Angeles.Google Scholar
- Queyranne, M., & Schulz, A.S. (1994). Polyhedral approaches to machine scheduling. Technical report, Preprint No. 408/1994, Department of Mathematics, Technical University of Berlin, Germany.Google Scholar
- Ullrich, C. A. (2013a). Issues in supply chain scheduling and contracting. Berlin: Springer.Google Scholar
- Volpe, R., Roeger, E., & Leibtag, E. (2013). How transportation costs affect fresh fruit and vegetable prices. USDA-ERS (Economic Research Service), Economic Research Report 160.Google Scholar
- Zhong, X., & Jiang, D. (2016). Integrated scheduling of production and distribution with release dates and capacitated deliveries. Mathematical Problems in Engineering, 2016, 9315197.Google Scholar